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Journal receives papers in continuous flow and we will consider articles from a wide range of Information Technology disciplines encompassing the most basic research to the most innovative technologies. Please submit your papers electronically to our submission system at http://jatit.org/submit_paper.php in an MSWord, Pdf or compatible format so that they may be evaluated for publication in the upcoming issue. This journal uses a blinded review process; please remember to include all your personal identifiable information in the manuscript before submitting it for review, we will edit the necessary information at our side. Submissions to JATIT should be full research / review papers (properly indicated below main title).

Journal of Theoretical and Applied Information Technology
August 2021 | Vol. 99 No.15

Title:	A DECENTRALIZED, LOW COMPUTATIONAL COST STRATEGY FOR COORDINATION AND SEARCH WITH A ROBOT FLOCK
Author:	FREDY H. MARTINEZ S
Abstract:	The coordination of a flock of robots is a high demand application in applications such as motion planning, navigation, herding (tracking and/or tracing), area coverage (exploration, search and rescue, etc.), object transportation (surrounding and moving together), and compound tasks, all of which are currently heavily researched in robotics. Many approaches have been proposed to solve this problem, but they largely compromise system characteristics such as fault tolerance, capacity, efficiency, and in particular cost, since real implementations require special hardware. This paper proposes a coordination strategy for a system composed of small robots of minimalist design under the condition of minimum processing and sensing capacity. The communication requirements have been limited to a local communication strategy sufficient to achieve the relative orientation of each swarm member. The usefulness of the scheme is evaluated by simulation in specialized search tasks in an unknown region. The results show the high capability of the scheme and the ease of implementation on real prototypes.
Keywords:	Collective movement, Flocking, Leader-follower, Swarm robotics, Self-organizing systems
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	RISK ASSESSMENT OF INVESTMENT LOSSES AIMED AT THE DEVELOPMENT OF SMART CITY SYSTEMS
Author:	LAKHNO V., KARTBAYEV T., MALYUKOV V., USKENBAYEVA R., TOGZHANOVA K., ALIMSEITOVA ZH., BEKETOVA G., TURGYNBAYEVA A.
Abstract:	In the article is suggested a model for the computing core for the decision support system (DSS) in assessing the risks of investment loss during the dynamic planning (DP) of SmartCity development. Unlike existing solutions, the suggested model gives specific recommendations for assessing the risks of loss. If the risk forecast is unsatisfactory, flexible adjustment of the investment process parameters is possible in order to achieve an acceptable financial result for the parties. The novelty of scientific results consists in the fact that for the first time it is suggested to apply a new class of bilinear multi-step games. This class allowed us to adequately describe the process of risk assessment of investment loss, using the example of dynamic planning for the placement of players' financial resources in SmartCity projects. A distinctive feature of the considered approach is the use of tools based on the solution of a bilinear multi-step game of both quality with several terminal surfaces and a degree game solved in the class of mixed strategies. Computational experiments were carried out in the Maple mathematical modeling package. An DSS was developed in which a risk assessment model is implemented. The developed DSS allows you to reduce the discrepancy between the data of forecasting the risks of investment loss during SmartCity and real return on investment. The model presented in the paper is based on solving a linear multistep degree game using the results of solving a multistep quality game with multiple terminal surfaces. The problem in the article is considered in the statement, standard for a multi-step game.
Keywords:	Risk Assessment, Investment Loss, Multi-Step Games With a Quality Of Several Terminal Surfaces, Decision Support System
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	A MATHEMATICAL MODEL TO EVALUATE DELAY AND POWER CONSUMPTION OF S-ALOHA PROTOCOL IN AN IOT ENVIRONMENT
Author:	ABDELLAH ZAALOUL, MOHAMED BEN EL AATTAR
Abstract:	During the last decade the Internet of Things (IoT) has taken on great importance in human life flooded by the increased use of new technologies. IoT aims to make users' lives more comfortable. To achieve this objective, the researchers were interested in the communication protocols used which play an important role in the guarantee of quality for the services offered. MAC protocols are in this sense those that have received the most importance. In this context, we are interested in this paper to evaluate the performance in latency and in energy consumption of one of the most used Mac protocols which is the Slotted-Aloha protocol. For this, we propose a mathematical model based on Markov chains which allows to take into account the different aspects of the protocol studied in the IoT environment. The theoretical evaluation of the delay and of the energy consumption are made and a numerical analysis is given for the validation of our model.
Keywords:	IOT, Delay, Power Consumption, Slotted-Aloha, Markov Chain.
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	A NOVEL APPROACH BASED ON ACTIVE CONSTRAINT FOR MINIMIZING VAR IN THE PORTOFOLIO OPTIMIZATION PROBLEM
Author:	RIRI SYAFITRI LUBIS, HERMAN MAWENGKANG, OPEN DARNIUS, MARDININGSIH
Abstract:	The portfolio optimization mathematical model is more frequently expressed with an eye to minimize the Value at Risk (VaR). Markowitz's difficulties in managing the quadratic programming model were alleviated by recent advances in algorithmic analysis, which sparked interest in overcoming real constraints in portfolio selection by introducing a linear risk function. The point of this article is to address the issue of portfolio selection of minimum transaction lots. An improved search algorithm appertaining to active constraints is presented to interpret the integer programming model. The algorithm leads by solving the relaxed problem in order to reach a settlement that is similar to a continuous solution.
Keywords:	Mixed Integer Programming, Portfolio Optimization, Active Constrained
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	BI DASHBOARD TO SUPPORT DECISION MAKING ON PRODUCT PROMOTION FOR PAYMENT/PURCHASE TRANSACTIONS ON E-BANKING
Author:	SEPTIAN EKA ADY BUANANTA, ANDRY CHOWANDA
Abstract:	Product promotion is one of the business strategies expected to make customers use e-banking in every transaction process. Therefore, the bank must adjust the customer expectations and provide suitable services based on transaction history to increase the use of e-banking. One of the solutions with the right approach to such a problem is creating a smart Business Intelligence system that comes in BI Dashboard. By highlighting the key performance and indicators of transactional data, managers are expected to gain information or insights that can be used as a reference to give more accurate promotions. Finally, cluster analysis using the K-Means algorithm is also provided to group data against its respective characteristics that may have been unnoticed. Then, stakeholders can translate the characteristics of each cluster into their business perspective. Based on the test results by comparing two samples from the pretest and posttest results (paired T-Test), the knowledge value of the management team after implementing the BI Dashboard increased to 95.2%. Therefore, the BI Dashboard with the K-Means algorithm is the suitable method to be applied as a decision making for e-banking product promo recommendations for payment and purchase transactions.
Keywords:	Business Intelligence, E-Banking, K-Mean, Product Promotion, Transaction Data
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	PROVING THE CORRECTNESS CONDITIONS OF THE THREE-WAY HANDSHAKE PROTOCOL USING COMPUTATIONAL TREE LOGIC
Author:	AHMAD ALOMARI, RAFAT ALSHORMAN
Abstract:	The three-way handshake protocol is widely used especially as a part of complex communication and security systems. It is used to establish a connection between a client and a server under specific rules and constraints. In this research, we used the NuSMV model checker along with Computational Tree Logic (CTL) to verify the correctness of the three-way handshake protocol over specific correctness conditions and properties. The results showed that the proposed protocol satisfied all correctness conditions except δ_9, δ_11, and δ_12. Furthermore, the proposed automated verification approach aims to verify the correctness of a finite number of clients each of them iterated infinitely often.
Keywords:	CTL, Model Checking, Nusmv, Three-Way Handshake Protocol, Correctness Conditions, Kripke Model.
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	DEVELOPMENT OF INTELLIGENT INFORMATION SYSTEM OF ASSESSING THE NEGATIVE IMPACT OF INDUSTRIAL EMISSIONS ON THE PUBLIC HEALTH
Author:	OLGA SHVETS, ALINA BUGUBAYEVA, SAULE RAKHMETULLINA, WALDEMAR WOJCIK
Abstract:	The following investigation is based upon the treated patients’ data of the East-Kazakhstan region and information about the level of emissions in Ust-Kamenogorsk for the same period. The analysis resulted in correlation between specific diseases and industrial emissions. The study of the influence of environmental factors on the health of the population and the risk of disease is an urgent and demanded task. The idea of the work: to identify and quantify the relationship between atmospheric pollution by emissions of harmful substances from industrial enterprises with the damage caused to the health of the population. The purpose of the work: to develop, on the basis of theoretical research and processing of statistical materials, a methodology for predicting the negative impact of harmful emissions on the health of the population. The research was constructed with neuro-net modelling technology. “Intelligent information system of Assessing the negative impact of industrial emissions on human health (on the example of Ust-Kamenogorsk data)” based on neural network technology was created to automate tasks. The information system was developed using the C # programming environment. A certificate on data registration in the state register of copyrighted objects of the Republic of Kazakhstan No. 16777, from April 20, 2021 (see Figure 10) was received.
Keywords:	Neuro-net, Modelling, Ecological Monitoring, Health, Ecological Predicting
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	A CONCEPTUAL FRAMEWORK FOR AUTOMATED ASSISTIVE LEARNING USING ROBOT FOR AUTISM: A REVIEW
Author:	SITI AZIRAH ASMAI, NORASIKEN BAKAR, SAZILAH SALAM, NOR HAFIZAH ADNAN, MUHAMMAD HAFIZI MOHD ALI
Abstract:	As rapid advancements continuously alter the way we do things and enhance our daily activities, these technologies are merely tailored for normal citizens causing people with special needs, including people with autism, to be left behind. In this 4IR era, technology such as robot technology is advancing very fast and this offers a very big opportunity for inclusion of students with special needs especially ASD since research has shown that ASD children gained advantages in many aspects by using robots in their learning process. This paper aims to present a list of existing robots that can be used to support ASD education, existing robot interactive recognition features that can be used to support ASD education, and elements of a framework for enhancing existing robot technology and recognition features to provide effective automated assistive learning technology for ASD education. A review of existing robots and robot recognition features that can be used to support ASD education were conducted. The review continued to reveal the elements of a framework for enhancing existing robot technology with recognition features to provide effective automated assistive learning technology for ASD education. The results are a report on four generations of robots and six humanoid robots that can be used for autism assistive learning. The outcome also includes eye tracking, face recognition and emotion recognition which are three important recognition methods embedded in the robots to make it interactive to humans and therefore suitable to be used to support ASD assistive learning. Last but not least are two conceptual frameworks proposed for enhancing learning effectiveness by using robots. The conceptual framework aims to provide automated assistive learning technology by enhancing existing robot technology and integrating new recognition features for ASD learning purposes.
Keywords:	Humanoid Robot, 4IR, Autism, Assistive Learning, Recognition
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	SOLVING TRAVELING SALESMAN PROBLEM USING GENETIC ALGORITHM BASED ON EFFICIENT MUTATION OPERATOR
Author:	AHMAD BANY DOUMI, BASEL A. MAHAFZAH, HAZEM HIARY
Abstract:	The Traveling Salesman Problem (TSP) is a Combinatorial Optimization Problem (COP), which belongs to NP-hard problems and is considered a typical problem for many real-world applications. Many researchers used the Genetic Algorithm (GA) for solving the TSP. However, using a suitable mutation was one of the main obstacles for GA. This paper proposes for GA an Efficient Mutation (GA-EM) for solving TSP. The efficient mutation can balance between deeply searching and preventing stuck on local optima to ensure a better convergence rate and diversity. Therefore, in this paper, a local search method based on three neighborhood structure operators; namely, transpose, shift-and-insert, and swap, is proposed to produce the efficient mutation for GA. The performance of the proposed algorithm is validated by three TSP datasets; including, TSPLIB, National TSPs, and VLSI Data Set. These datasets have different graphs’ structures and sizes. The sizes of the datasets range from 150 to 18512 cities. For comparative evaluation, the results obtained from the proposed GA-EM are compared with those obtained by four relatively recent approaches using the same TSP instances. These approaches are the Modernised Genetic Algorithm for solving TSP (MGA-TSP), List-Based Simulated Annealing algorithm (LBSA), Symbiotic Organisms Search optimization algorithm based on Simulated Annealing (SOS-SA), and Multiagent Simulated Annealing algorithm with Instance-Based Sampling (MSA-IBS). The GA-EM outperformed these approaches in all used TSP instances in terms of accuracy.
Keywords:	Genetic Algorithm, Mutation Operator, Neighboring Operator, Simulated Annealing Algorithm, Traveling Salesman Problem
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	MACHINE LEARNING-BASED FRAMEWORK FOR AUTOMATIC MALWARE DETECTION USING ANDROID TRAFFIC DATA
Author:	UZOMA RITA ALO, HENRY FRIDAY NWEKE, SYLVESTER I. ELE
Abstract:	One of the greatest challenges facing various organizations and institutions is information security. Attackers have devised means to steals mobile user identity by developing malware that might be inadvertently installed by users due to the open source nature of android operating system causing financial loses. Although various machine learning algorithms have been proposed recently for malware detection, it is challenging to detection malicious apps with single classification model. In this paper, we propose to detect malicious apps in android traffic using four (4) different machine learning algorithms. The proposed approach was evaluated on comprehensive and publicly available dataset. The result obtained shows that decision tree and tree based ensemble algorithms produced superior results when compared with support vector machine and logistic regression models. The results suggest the impact of multiple classification algorithms to improve the performance of malware detection system. The finding can be utilized to guide security expert on the use of machine learning methods to detect malicious software.
Keywords:	Malware Detection, Machine Learning Algorithms, Mobile Network Traffic, Multiple Classifier System, Cybersecurity Systems
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	PCA AND PROJECTION BASED HAND GESTURE RECOGNITION
Author:	ASKHAT AITIMOV, ZHASDAUREN DUISEBEKOV, SHIRALI KADYROV, CEMIL TURAN
Abstract:	Developing hand gesture recognition algorithms, and more generally, pattern recognition algorithms is a very active area of research in computer vision. There are various approaches and techniques to the recognition problem among researchers. In this manuscript, our objective is to develop a novel Principal Component Analysis based hand gesture recognition algorithm, and compare its performance against k-Nearest Neighbor classifier and Sparse Representation based Classifier. The proposed algorithm makes use of linear triplet loss embedding and projections onto subspaces. An open source HandReader dataset consisting of 500 labeled images with 10 signs from American Sign Language is split into a training set with 100 images and a test set with 400 images. The proposed algorithm outperforms with 95% accuracy. This shows that the proposal methodology might be effective in computer vision when there is relatively small amount of data is available. It is expected that approaches similar to the current one will contribute the emergence of machine learning algorithms with Principal Component Analysis based techniques.
Keywords:	Computer Vision, Sign Language, Hand Gesture Recognition, Human-Computer Interaction, Triplet Loss, Stochastic Gradient Descent, PCA-TP, SRC, kNN
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	DEEP GRAPH EMBEDDINGS IN RECOMMENDER SYSTEMS: A SURVEY
Author:	AMINA SAMIH, ABDERRAHIM GHADI, ABDELHADI FENNAN
Abstract:	In recent decades, the increasing quantity of products and services offered the possibility of collecting significant amounts of data, which require new techniques to sort it. Rather than manually filter these large quantities of information, it provides changes over time. Recommender systems help suggest articles to read on smartphones, posts to watch on Facebook, books to buy on Amazon. Their goal is to personalize data to increase the use of a service or to enable more sales. Their influence is not just a technical and commercial necessity. They have also become a part of the evolution of the human mass and his\her ideas. Because a book or a newspaper is not just a commercial object, many current recommendation techniques are challenged by information overload, which poses many issues like high cost, slow processing of data, and low time complexity. For this reason, many researchers in this field use graph embeddings algorithms in the recommendation area, as the last few years have also seen the success of these algorithms, especially the ones based on deep learning. Current recommender systems based on these algorithms have shown that they can obtain exciting results and improve the quality of recommendations offered to users. In this survey, we present an overview of recommender systems and graph embeddings based on deep learning. Then we provide a literature review of recent recommendations works based on deep graph embeddings to make a pragmatic analysis and showings common limitations.
Keywords:	Recommender Systems, Graph Embeddings, Deep Learning, Deep Graph Embeddings, Hybrid Recommendation.
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	THE IEEE 802.15.4 STANDARD IN INDUSTRIAL APPLICATIONS: A SURVEY
Author:	Khalid EL GHOLAMI, Yassine MALEH, Imade Fahd-Eddine FATANI
Abstract:	The IEEE 802.15.4 has become the de facto medium access standard for industrial applications. It’s a widely used standard in countless real implementations. The success of the IEEE 802.15.4, specifically designed for low-rate and low power and lossy networks, pushes many wireless industrial solutions (e.g., ZigBee Alliance, ISA100 and WirelessHART) to adopt it or, at least, some of its features for wireless network access. This paper's primary goal is to provide a clear overview of research and development efforts related to the IEEE 802.15.4 standard in the context of Industrial Application. We explore the historical evolution of the standardization efforts of the IEEE 802.15.4 side-by-side with research efforts, mainly focusing on recent works, that improved this standard and contributed to making it relevant for the Industry 4.0 paradigm. This paper also shines a light on some problems and limitations raised by real world implementations in industrial environments. Finally, we discuss existing challenges in IWSN and important future research directions which can help practicing scientists and engineers in industrial networking in their future work.
Keywords:	IEEE 802.15.4; Industry 4.0; IWSN; IIoT; Performance; Scheduling; Coexistence; channel; determinism; reliability
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	DETECTION OF HEART DISEASE BY USING RELIABLE BOOLEAN MACHINE LEARNING ALGORITHM
Author:	Dr. M. BHEEMALINGAIAH, Dr. G. RAMA SWAMY, Dr. P. VISHVAPATHI, P. VENU BABU, E. NAGESWARA RAO, Dr. P. NAGESWARA RAO
Abstract:	Artificial Intelligence (A.I) is one of most exciting fields of computer engineering today. It is the science and technique used to make machine intelligent and it is vast and truly universal field. However, tremendous growth has been observed in this filed in past two decade owing to valuable contributions from variety of domains. It has numerous potential applications such as computer vision, medicine, philosophy, psychology, linguistics, automatic programming, natural language processing, speech processing and robotics, etc. Machine Learning takes training from natural events and helps in predicting any type of event and is a branch of Artificial Intelligence (AI). Over the past two decades, Machine Learning became a major source for information technology in developing applications, such as manufacturing industry for automation in assembly line, biometric recognition, handwriting recognition, medical diagnosis, speech recognition, text retrieval, natural language processing and Machine Learning is widely using in Data Science (DS), it is predominant and hotcake field of 21st century. Today all of use machine learning several times a day, without knowing it. Examples of such "ubiquitous" or "invisible" usage include search engines, customer-adaptive web services, email managers (spam filters), computer network security, and so on. Since last few decades Cardiovascular(Heart) Diseases (CVDs) has emerged as the most life-threatening diseases and proved to be fatal not only in India but throughout the whole world. In time detection, diagnosis and treatment of the disease needs a reliable, accurate and feasible system. In this paper we proposed Reliable Boolean Machine Learning Algorithm (RBMLA) by using novel approach to predict heat disease. Finally performance of RBMLA is measured by using various performance metrics like accuracy, precision, recall, sensitivity, specificity, reliability, F-score and ROC curve. It is shown that it gives better performance for given any new test data and new real time data. It has given better accuracy of 86%.
Keywords:	Support Vector Machine ,Naive Bayes algorithm, k-Nearest Neighbor Algorithm, Decision Tree Algorithm, Random Forest Algorithm, , Reliable Boolean Machine Learning Algorithm.
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	PUBLIC AND AUTOMATED FUNCTIONAL TESTING (CAPTCHA) WITH ANIMATIONS BASED ON FACIAL EXPRESSIONS
Author:	RODOLFO ROMERO-HERRERA, MANUEL OSWALDO LÓPEZ MARÍN, JOSÉ FÉLIX SERRANO TALAMANTES
Abstract:	The growing need to avoid the generation of false information on the internet forces service providers to have options, the reverse test being completely automatic to distinguish computers from humans (CATPCHA Completely Automated Public Turing test to tell Computers and Humans Apart), one of the most varied and preferred methods to achieve this goal. In this research, a version of CAPTCHA is implemented that meets all design requirements, such as the simplicity in solving the challenge and the complexity necessary to avoid being solved by an automatic program. This article contributes by adding a procedure with which the CATPCHA is regenerated every 2 minutes, changing the location of the images randomly, including the keyboard where the answer is entered. Another contribution is the use of icons with facial expressions using animated gifs that have the cognitive advantage of identifying human beings concerning machines. In addition, the use of image segmentation techniques is avoided using techniques and distortions, which did not affect the use and identification of CATPCHA. To verify the effectiveness of the proposal, several tests were implemented that verified the effectiveness of the method.
Keywords:	Captcha, test de Turing, distortional, facial expression, Bots.
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	THE DETERMINANTS OF CUSTOMER SATISFACTION AND INTENTION TO USE ON E-COMMERCE LOYALTY PROGRAM
Author:	ALBERT MILIANO, VIANY UTAMI TJHIN
Abstract:	In this modern age, most people prefer buying stuff online. Based on a survey, the percentage of dissatisfaction for e-Commerce is still high in number. The top reason that can be improved based on customer’s response was to increase the quality and frequency of a promotion. One of the strategies to accommodate this problem is through the implementation of a loyalty program system. A loyalty program is a marketing strategy that rewards the customer for their loyalty act. In this study, the factors influencing the perceived usefulness, ease of use, customer satisfaction, and intention to use are conducted from 182 respondents from the three most popular e-Commerce in Indonesia, Tokopedia, Bukalapak, and Shopee. Based on the study results, information quality and system quality influence perceived usefulness. System Quality and SAervice Quality influence Perceived Ease of Use. Information Quality, Reward Variation, Reward Value influence Customer Satisfaction. None of the variables in this research influences Intention to Use.
Keywords:	E-Commerce, Loyalty Program, Customer Satisfaction, Intention To Use
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	DESIGNING OF URBAN FARMING SYSTEMS BASED ON INTERNET OF THINGS
Author:	AHMAD NURUL FAJAR, RIYANTO JAYADI, EMIL ROBERT KABURUAN, MICHAEL BHUDIAWAN, ANAK AGUNG ISTRI KRISNA GANGGA DEWI, ALBERT SEBASTIAN, TASKIA FIRA INDRIASARI
Abstract:	Purpose of this study is to find out whether the design of information systems can help agricultural industrial processes, to find out how the use of IoT in agricultural industrial processes, and to find out how the design of an IoT-based information system can monitor plant status. System design using the Arduino Wemos D1 Microcontroller. The design of IoT and sensor designs and other schemes uses Axure as a medium for making prototype designs. UML design and flow diagrams using Visual Paradigm. Implementing the cloud as a medium of communication between the IoT concept and the system to be created. The benefits of the systems such as : Assist users in controlling plant maintenance both during planting and harvesting, Can make it easier for users to find out the status of the plant and the room temperature to keep it stable, and Can be expanded and developed into a product that can be used by the wider community in the urban agricultural industry
Keywords:	Urban Farming, Systems, IOT, Designing
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	SYNTHETIC DNA AS A SOLUTION TO THE BIG DATA STORAGE PROBLEM
Author:	MANAR SAIS, NAJAT RAFALIA, JAAFAR ABOUCHABAKA
Abstract:	In the last few years, we have witnessed unprecedented growth in data and gigantic amounts of data are being produced every day. By 2020, the amount of information we want to store it will be around 44 trillion gigabytes. on the one hand the data volumes continue to grow at an even higher speed, However, our traditional databases are limited in the storage and processing of this large and complex data and we do not have a reliable physical storage medium that can withstand the weather. On the other hand, the term Big Data is now the new natural resource and current analysis architectures face much greater challenges in terms of scalability, rapid ingestion, performance, processing and storage efficiency. In order to cope with these massive and exponentially increasing amounts of heterogeneous data generated more and more quickly, many researchers believe that they have found the solution to this problem, either develop and add an intelligent touch to the available technology, or have discovered solution effective in the field of chemistry, DNA for example. DNA molecules as information carriers have many strengths over traditional storage media. Its high storage density, large capacity, long term stability, potentially low maintenance costs, and other excellent features make it an ideal alternative for information storage, and it is expected to provide wide practicality in the future. In this article, we present a DNA storage technology designed to optimize the storage of huge amounts of data or what is called Big Data. We study its storage capacity for large amounts of data, its operating principle and its added value compared to available technologies.
Keywords:	Storage; Big data; DNA, Datasets;
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	FACTORS AFFECTING BEHAVIOR OF THE USE OF HEALTHCARE MOBILE APPLICATION TECHNOLOGY IN INDONESIAN SOCIETY
Author:	JAROT S. SUROSO, TETUKO CATON SUKMORO
Abstract:	During the Covid-19 pandemic, many people were worried about coming directly to the hospital to fear being exposed to Covid-19. Therefore, some people prefer to use digital platforms such as mobile healthcare applications to conduct consultations regarding illnesses and purchase drugs or redeeming drugs from prescriptions given by doctors online. The purpose of this study is to determine the factors that influence the use behavior mobile healthcare applications in Indonesia using the UTAUT2 method using the variable performance expectancy, effort expectancy, social influence, facilitating conditions, habit, behavioral intention, use behavior using moderating variables, namely age, gender, and location. The results of the test show that performance expectancy, social influence, facilitating conditions, and habit have a positive effect on behavioral intention. Likewise, the behavioral intention has a positive effect on use behavior.
Keywords:	Mobile Healthcare Application, UTAUT2, behavioral intention, use behavior, Covid-19
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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Title:	SECURITY THREATS TO PERSONAL DATA IN THE IMPLEMENTATION OF DISTANCE EDUCATIONAL SERVICES USING MOBILE TECHNOLOGIES
Author:	VASILY NIKOLAEVICH POPOV, VITALY NIKOLAEVICH VASILENKO, VICTOR ANATOLYEVICH KHVOSTOV, VLADIMIR VLADIMIROVICH DENISENKO, ALEKSEY VASILYEVICH SKRYPNIKOV, ANDREY VALENTINOVICH IVANOV, ALEXANDER NIKOLAEVICH BELYAEV, OKSANA GEORGIEVNA STUKALO
Abstract:	The purpose of the article is to develop a model of threats to the security of personal data in the implementation of distance educational services using mobile technologies. The model of threats to the security of personal data in the implementation of remote educational services using mobile technologies will allow forming requirements and recommendations for their protection and providing the initial data for the synthesis of the information security system, as a set of heterogeneous tools. Therewith, internal and external communications on data and management, the presence of a management system lead to the appearance of integrative effects and ensure the completeness and consistency of protection. The construction of a model of threats to the security of personal data in the implementation of distance educational services using mobile technologies is carried out by the method of information-logical analysis of existing approaches to the classification of threats to information security contained in the regulatory documents of regulators in the field of information security. The second method is the collection of data contained in domestic and international knowledge bases containing information about the vulnerabilities of mobile technologies used in the implementation of educational services and vectors of information security threats using these vulnerabilities. As a result of the work, a new classification scheme of information security threats has been formed, taking into account the peculiarities of personal data protection in the implementation of distance educational services using mobile technologies. The objectives of information security in the implementation of distance education services using mobile technologies have been analyzed and the analysis of possible technical measures for information protection has been carried out.
Keywords:	Distance Educational Service, Mobile Station, Security Gateway, Mobile Device Manager.
Source:	Journal of Theoretical and Applied Information Technology 15^th August 2021 -- Vol. 99. No. 15 -- 2021
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